中国电力资源跨区域优化配置模型研究
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摘要
中国电力资源与负荷分布呈逆向分布,电力资源主要分布在西部、北部地区,而负荷则主要分布在东部地区,由此造成中国电力工业供电成本高昂,风电消纳困难,输电损耗严重,电力投资臃肿等窘况。对社会而言,造成一系列负外部性效应,其提高了社会用电成本,降低了能源利用效率,也加剧了大气污染程度。如何协调电力资源与负荷分布,实现电力资源的跨区域优化配置已经成为制约电力工业低碳化、可持续发展的关键问题。
传统模式下电力资源的跨区域配置主要依赖一次能源运输的模式实现,远距离输电技术的发展在一定程度上缓解了传统能源运输通道的压力,丰富了电力资源跨区配置的形式。中国正致力建设跨区域输电通道,强化区域间电网架构,通过区域间的发电置换优化清洁能源的利用水平,缓解受端区域发电排污压力。在此背景下,围绕中国电力资源跨区域优化配置展开研究,重点研究了电力资源与负荷分布的协调状况,区域间电力资源配置要素的因果传递关系,区域间电源与电网协调规划,大规模风电跨区域消纳以及跨区域配置下发电企业利益分配、交易谈判等问题。
电力资源与负荷分布协调的程度决定了电力资源跨区域配置的难度与深度。围绕中国电力负荷与煤炭、水能、风能三类能源的分布进行分析,借助基尼系数对负荷与能源分布的协调程度进行测算。分析结果表明煤炭、水能、风能的分布与负荷的协调程度都比较低,但水电与风电开发的倾向性在一定程度上缓解了一次能源与负荷分布的不协调。
电力资源跨区域配置受到输电线路容量、输电价格、风电消纳水平等客观因素的制约,这些因素影响了能源产业链实物量与价值量的传递与反馈,有鉴于此,构建了区域间电力资源供需的系统动力学模型。通过因果关系图与流积图描绘系统中各变量之间因果传递关系,借助Vensim软件对区域间电力资源供需关系与价格的变化趋势进行仿真模拟,并以煤炭供应、经济增长率、风电利用小时以及输电容量等因素为敏感因子对电力资源的跨区域配置状况进行敏感性分析。
电力资源跨区域配置受区域间电力规划的限制,反之,电力规划也在一定程度上左右了电力规划的走势。以规划年内发电综合成本最小为目标,考虑了电力平衡、发电备用、建设成本的约束条件,构建了多类型发电机组与跨区域输电网协调发展的优化模型,通过优化协调了电源与电网的建设容量与建设时点,既保证区域间电力资源配置的发展进程,提高能源综合利用效率,同时避免了因发电与电网建设不协调而导致投资的浪费。
区域间输电通道的建设扩大了风电的消纳空间,在一定程度上降低了弃风水平。中短期而言,风电可与火电打捆通过输电专线输送至受端区域；以机组组合模型为基础,考虑风电调峰、输电功率波动等约束构建了风火联合外送的调度模型,对参与电力外送的风电与火电进行实时输出功率的协调优化。中长期而言,风电的消纳可以借鉴电力库模式；配合需求侧负荷对电价的响应机制以及储能系统对风电反负荷特性的调节能力,通过改变负荷与出力的时间分布以扩大风电的消纳水平。
电力资源跨区域配置将影响电力市场参与者的市场份额,因此,理顺各市场参与者的利益关系是推进电力资源跨区域配置的基础。关于风电与火电联合外送中双方利润分配的问题,以双方对联盟效益的贡献度为依据,借助Shapley值法与核心法对双方进行利益分配,并以区域碳交易价差以及输电波动约束作为敏感因子,研究其对利益分配份额的影响。关于区域间火电机组发电权交易谈判的问题,基于Zeuthen决策以及贝叶斯学习提出一个双方逐步估算对方底价,逐步收敛双方报价差的谈判模型,尽可能使双方效用达到最大化。
The distribution of power resources and power load in China are reverse. Power resources are mainly distributed in the west and north regions, while the power load are mainly in east China. The resulting predicament causes a high cost of China's power generation industry, difficulties in wind power accommodation, a high transmission losses and the inflexibility of power investment. This resource structure has a negative effect on the whole society, the power cost increased, the energy efficiency reduced and the air pollution has aggravated. In order to optimize the allocation of inter-regional power resources, how to coordinate the distribution of power resources and power load has become the key issue of achieving a low-carbon and sustainable development of China's power industry.
In the traditional model, the inter-regional allocation of power resources mostly relies on the transportation of primary energy. The development of long distance power transmission has relived the pressure on traditional energy transportation mode to some extent. China is devoting to the construction of inter-regional transmission channel and strengthens the inter-regional grid architecture, to improve clean energy utilization by optimizing inter-regional generation replacement and alleviate the pressure on power generation pollution. Under such background, based on the optimal allocation of inter-regional power resources in China, this dissertation focuses on the coordination between power resources and power load distribution, the causality in essential factors of inter-regional power resources allocation, the coordination between inter-regional power generation and power grid, and the inter-regional accommodation of large-scale wind power, the profit distribution and trade negotiation between power generation enterprises in the inter-regional allocation mode.
The coordination degree for the distribution of power resources and power load determines the difficulty and depth of inter-regional allocation of power. This dissertation analyzes the distribution between power load and coal, hydro power, wind power, calculating the coordination degree of power load and energy distribution by Gini coefficient. The result indicates that the coordination degree between these energies (coal, hydro power and wind power) distribution and power load are relatively low. However, the exploitation of hydro power and wind power alleviated the incongruity between primary energy and power load distribution.
Inter-regional allocation of power resources is constrained by objective factors like transmission capability, transmission price, and wind power accommodation level, etc. This constraint affects the transmission and feedback of physical quantity and value quantity in energy industry chain. Accordingly, this dissertation establishes a system dynamics model of inter-regional power supply and power demand. Describing the transitive relation between each factor through causal loop and flow-stock diagram, and simulate the variation trend of the relation between inter-regional power supply-demand and price by Vensim. With coal supply, economic growth rate, utilization hours of wind power, and transmission capacity as sensitivity factors, a sensitive analysis of inter-regional power allocation is performed.
The allocation of inter-regional power resources is limited by the power planning; conversely, it also affects the trends of power planning to a certain extent. With the goal of minimizing the power generation cost in the planning year, considering power balance, backup power, generation reserve and construction cost as constraints, this dissertation establishes an optimization model for coordinating development between multi-type generators and inter-regional power transmission network. By optimizing the coordination in the construction capacity and construction timing of power generation and power grid, the development of inter-regional allocation of power resource is guaranteed, the energy utilization efficient increased, while avoiding the wasteful investment resulting from the discordance of power generation and power grid construction.
The construction of inter-regional transmission channel expands the capacity of wind power accommodation and reduces wind power curtailment to a certain context. For short and medium term, wind power can be delivered to the consumer by banding together with thermal power through transmission line. Based on unit commitment (UC) model, considering wind power peak regulation and the fluctuation of transmission power as constraints, a dispatching model of power delivering, which combines wind power with thermal power is built. This model can optimize the coordination of a real-time output power from combined power delivering. For the medium to long term, the accommodation of wind power can learn from power pool mode. Cooperate with the mechanism of customer load demand respond to the electricity price and the adjustment of wind power's anti load characteristic in energy storage system, the accommodation of wind power can be expanded by changing the time distribution of the load and the output.
The inter-regional allocation of power resources will affect the share distribution of the electricity market participants, therefore, rationalize the interests of all market participants is the basis of promoting inter-regional allocation of power resources. The profit-sharing in combined electricity delivering mode:wind power band with thermal power, can be distributed based on the contribution to the whole union benefits with Shapley-value and core method. Researching on the effect of profit-sharing in combined electricity delivering mode by setting inter-regional carbon trading spread and transmission fluctuation constraint as sensitivity factors. Issues on the negotiation of generation rights trade in inter-regional thermal power unit, this dissertation proposes a negotiation model based on Zeuthen strategy and Bayesian learning. In this model, both parties gradually estimate the base price of the opponent to reduce the price difference, in order to maximize the utility of both parties.
传统模式下电力资源的跨区域配置主要依赖一次能源运输的模式实现,远距离输电技术的发展在一定程度上缓解了传统能源运输通道的压力,丰富了电力资源跨区配置的形式。中国正致力建设跨区域输电通道,强化区域间电网架构,通过区域间的发电置换优化清洁能源的利用水平,缓解受端区域发电排污压力。在此背景下,围绕中国电力资源跨区域优化配置展开研究,重点研究了电力资源与负荷分布的协调状况,区域间电力资源配置要素的因果传递关系,区域间电源与电网协调规划,大规模风电跨区域消纳以及跨区域配置下发电企业利益分配、交易谈判等问题。
电力资源与负荷分布协调的程度决定了电力资源跨区域配置的难度与深度。围绕中国电力负荷与煤炭、水能、风能三类能源的分布进行分析,借助基尼系数对负荷与能源分布的协调程度进行测算。分析结果表明煤炭、水能、风能的分布与负荷的协调程度都比较低,但水电与风电开发的倾向性在一定程度上缓解了一次能源与负荷分布的不协调。
电力资源跨区域配置受到输电线路容量、输电价格、风电消纳水平等客观因素的制约,这些因素影响了能源产业链实物量与价值量的传递与反馈,有鉴于此,构建了区域间电力资源供需的系统动力学模型。通过因果关系图与流积图描绘系统中各变量之间因果传递关系,借助Vensim软件对区域间电力资源供需关系与价格的变化趋势进行仿真模拟,并以煤炭供应、经济增长率、风电利用小时以及输电容量等因素为敏感因子对电力资源的跨区域配置状况进行敏感性分析。
电力资源跨区域配置受区域间电力规划的限制,反之,电力规划也在一定程度上左右了电力规划的走势。以规划年内发电综合成本最小为目标,考虑了电力平衡、发电备用、建设成本的约束条件,构建了多类型发电机组与跨区域输电网协调发展的优化模型,通过优化协调了电源与电网的建设容量与建设时点,既保证区域间电力资源配置的发展进程,提高能源综合利用效率,同时避免了因发电与电网建设不协调而导致投资的浪费。
区域间输电通道的建设扩大了风电的消纳空间,在一定程度上降低了弃风水平。中短期而言,风电可与火电打捆通过输电专线输送至受端区域；以机组组合模型为基础,考虑风电调峰、输电功率波动等约束构建了风火联合外送的调度模型,对参与电力外送的风电与火电进行实时输出功率的协调优化。中长期而言,风电的消纳可以借鉴电力库模式；配合需求侧负荷对电价的响应机制以及储能系统对风电反负荷特性的调节能力,通过改变负荷与出力的时间分布以扩大风电的消纳水平。
电力资源跨区域配置将影响电力市场参与者的市场份额,因此,理顺各市场参与者的利益关系是推进电力资源跨区域配置的基础。关于风电与火电联合外送中双方利润分配的问题,以双方对联盟效益的贡献度为依据,借助Shapley值法与核心法对双方进行利益分配,并以区域碳交易价差以及输电波动约束作为敏感因子,研究其对利益分配份额的影响。关于区域间火电机组发电权交易谈判的问题,基于Zeuthen决策以及贝叶斯学习提出一个双方逐步估算对方底价,逐步收敛双方报价差的谈判模型,尽可能使双方效用达到最大化。
The distribution of power resources and power load in China are reverse. Power resources are mainly distributed in the west and north regions, while the power load are mainly in east China. The resulting predicament causes a high cost of China's power generation industry, difficulties in wind power accommodation, a high transmission losses and the inflexibility of power investment. This resource structure has a negative effect on the whole society, the power cost increased, the energy efficiency reduced and the air pollution has aggravated. In order to optimize the allocation of inter-regional power resources, how to coordinate the distribution of power resources and power load has become the key issue of achieving a low-carbon and sustainable development of China's power industry.
In the traditional model, the inter-regional allocation of power resources mostly relies on the transportation of primary energy. The development of long distance power transmission has relived the pressure on traditional energy transportation mode to some extent. China is devoting to the construction of inter-regional transmission channel and strengthens the inter-regional grid architecture, to improve clean energy utilization by optimizing inter-regional generation replacement and alleviate the pressure on power generation pollution. Under such background, based on the optimal allocation of inter-regional power resources in China, this dissertation focuses on the coordination between power resources and power load distribution, the causality in essential factors of inter-regional power resources allocation, the coordination between inter-regional power generation and power grid, and the inter-regional accommodation of large-scale wind power, the profit distribution and trade negotiation between power generation enterprises in the inter-regional allocation mode.
The coordination degree for the distribution of power resources and power load determines the difficulty and depth of inter-regional allocation of power. This dissertation analyzes the distribution between power load and coal, hydro power, wind power, calculating the coordination degree of power load and energy distribution by Gini coefficient. The result indicates that the coordination degree between these energies (coal, hydro power and wind power) distribution and power load are relatively low. However, the exploitation of hydro power and wind power alleviated the incongruity between primary energy and power load distribution.
Inter-regional allocation of power resources is constrained by objective factors like transmission capability, transmission price, and wind power accommodation level, etc. This constraint affects the transmission and feedback of physical quantity and value quantity in energy industry chain. Accordingly, this dissertation establishes a system dynamics model of inter-regional power supply and power demand. Describing the transitive relation between each factor through causal loop and flow-stock diagram, and simulate the variation trend of the relation between inter-regional power supply-demand and price by Vensim. With coal supply, economic growth rate, utilization hours of wind power, and transmission capacity as sensitivity factors, a sensitive analysis of inter-regional power allocation is performed.
The allocation of inter-regional power resources is limited by the power planning; conversely, it also affects the trends of power planning to a certain extent. With the goal of minimizing the power generation cost in the planning year, considering power balance, backup power, generation reserve and construction cost as constraints, this dissertation establishes an optimization model for coordinating development between multi-type generators and inter-regional power transmission network. By optimizing the coordination in the construction capacity and construction timing of power generation and power grid, the development of inter-regional allocation of power resource is guaranteed, the energy utilization efficient increased, while avoiding the wasteful investment resulting from the discordance of power generation and power grid construction.
The construction of inter-regional transmission channel expands the capacity of wind power accommodation and reduces wind power curtailment to a certain context. For short and medium term, wind power can be delivered to the consumer by banding together with thermal power through transmission line. Based on unit commitment (UC) model, considering wind power peak regulation and the fluctuation of transmission power as constraints, a dispatching model of power delivering, which combines wind power with thermal power is built. This model can optimize the coordination of a real-time output power from combined power delivering. For the medium to long term, the accommodation of wind power can learn from power pool mode. Cooperate with the mechanism of customer load demand respond to the electricity price and the adjustment of wind power's anti load characteristic in energy storage system, the accommodation of wind power can be expanded by changing the time distribution of the load and the output.
The inter-regional allocation of power resources will affect the share distribution of the electricity market participants, therefore, rationalize the interests of all market participants is the basis of promoting inter-regional allocation of power resources. The profit-sharing in combined electricity delivering mode:wind power band with thermal power, can be distributed based on the contribution to the whole union benefits with Shapley-value and core method. Researching on the effect of profit-sharing in combined electricity delivering mode by setting inter-regional carbon trading spread and transmission fluctuation constraint as sensitivity factors. Issues on the negotiation of generation rights trade in inter-regional thermal power unit, this dissertation proposes a negotiation model based on Zeuthen strategy and Bayesian learning. In this model, both parties gradually estimate the base price of the opponent to reduce the price difference, in order to maximize the utility of both parties.
引文
[1]Zhang Yan, Zhang Jinyun, Yang zhifeng, et al. Analysis of the distribution and evolution of energy supply and demand centers of gravity in China[J]. Energy Policy, 2012,49:695-706.
[2]Liu Jinpeng, Niu Dongxiao, Song Xiaohua. The energy supply and demand pattern of China:A review of evolution and sustainable development[J]. Renewable & Sustainable Energy Review,2013,25,220-228.
[3]张运洲.我国跨区域电力资源配置前景分析[J].中国电力,2004,37(9)：5-7.
[4]Froggatt Antony. The climate and energy security implications of coal demand and supply in Asia and Europe[J]. Asia Europe Journal,2013,11(3):285-303.
[5]Sun Mei, Han Dun, Li Dandan, et al. The general evolving model for energy supply-demand network with local-world[J]. International Journal of Modern Physics C,24(10):75-89.
[6]王建军,李莉,谭忠富,等.电力需求侧响应利益联动机制的系统动力学模拟[J].系统工程理论与实践,2011,31(12)：2287-2295.
[7]Kahen G M, Lehman M, Ramil J F, et al. System dynamics modelling of software evolution proeesses for policy investigation:Approach and example[J]. Journal of Systems and Software,2001,50(3):271-281.
[8]Saleh M, Oliva R, Kampmann C E, et al. A comprehensive analytical approaeh for policy analysis of system dynamics models[J]. European Journal of Operational Researeh,2010,203(3):673-683.
[9]Shen Q P, Chen Q, Tang B S, et al. A system dynamics model for the sustainable land use planning and development[J]. Habitat Intern ational,2009,33(1):15-25.
[10]李连德.中国能源供需的系统动力学研究[D].沈阳：东北大学,2009.
[11]Anindya Bhattacharya, Satoshi Kojima. Power sector investment risk and renewable energy:A Japanese case study using portfolio risk optimization method[J]. Energy Policy,2012,40:69-80.
[12]Lin Fan, Catherine S. Norman, Anthony G. Patt. Electricity capacity investment under risk aversion:A case study of coal, gas, and concentrated solar power[J]. Energy Economics,2012,34(1):54-61.
[13]Zhang Dongjie, Liu Pei, Ma Linwei, et al. A multi-period modelling and optimization approach to the planning of China's power sector with consideration of carbon dioxide mitigation[J]. Computers and Chemical Engineering,2012,37: 227-247.
[14]Liu Ye, Huang Guohe, Cai Yanpeng, et al. An inexact mix-integer two-stage linear programming model for supporting the management of a low-carbon energy system in China[J]. Energies,2011,4(10):1657-1686.
[15]Chen C, Li Y P, Huang G H, et al. A robust optimization method for planning regional-scale electric power systems and managing carbon dioxide[J]. Electrical Power and Energy Systems,2012,40(1):70-84.
[16]Tolis Athanasios I., Rentizelas Athanasios A.. An impact assessment of electricity and emission allowances pricing in optimised expansion planning of power sector portfolios[J]. Applied Eneygy,2011,88(11):3791-3806.
[17]Masoud Hasani-Marzooni, Seyed Hamid Hosseini. Dynamic model for market-based capacity investment decision considering stochastic characteristic of wind power[J]. Renewable Energy,2011,36(8):2205-2219.
[18]Yu Y X, Wang J R, Lv X Y. Security value based expansion planning of power system with integration of large-scale wind power[J]. Science China-Technological Sciences,2012,55(7):1908-1922.
[19]Alonso Monica, Amaris Hortensia, Alvarez-Ortega C. A multiobjective approach for reactive power planning in networks with wind power generation[J]. Renewable Energy,2012,37(1):180-191.
[20]袁建党,袁铁江,晁勤,等.电力市场环境下大规模风电并网系统电源规划研究[J].电力系统保护与控制,2011,39(5)：22-26.
[21]Shrestha G B, Fonseka P A J. Congestion-driven transmission expansion in competitive power markets[J]. IEEE Trans, on Power Systems,2003,19(3): 1658-1665.
[22]Bent Russell, Toole G. Loren, Berscheid Alan. Transmission network expansion planning with complex power Flow Models[J]. IEEE Transactions on Power Systems,2012,27(2):904-912.
[23]Zhao Jun Hua, Foster John, Dong Zhao Yang, et al. Flexible Transmission Network Planning Considering Distributed Generation Impacts[J]. IEEE Transactions on Power Systems,2011,26(3):1434-1443.
[24]Leou Rong-ceng. A multi-year transmission planning under a deregulated market[J]. International Journal of Electrical Power & Energy Systems,2011,33(3):708-714.
[25]Fan Hong; Cheng Hao-zhong. Multistage transmission network expansion planning in competitive electricity market based on bi-level programming method[J]. European Transactions on Electrical Power,2011,21(5):1719-1730.
[26]高赐威,程浩忠,王旭.考虑场景发生概率的柔性约束电网规划模型[J].中国电机工程学报,2004,24(11)：34-38.
[27]Raby Mauricio, Rios Sebastion, Jerardino Samuel. Integrating large wind farms into transmission planning of hydrothermal system[J]. Journal of Energy Engineering-ASCE,2009,135(3):89-97.
[28]Yu H, Chung C Y, Wong K P, et al. A Chance Constrained Transmission Network Expansion Planning Method With Consideration of Load and Wind Farm Uncertainties[J]. IEEE Transactions on Power Systems,2009,24(3):1568-1576.
[29]钟庆,吴捷,黄武忠,等.动态规划在电力建设项目投资决策中的应用[J].电网技术,2002,26(8)：48-51.
[30]孙寿广.低碳经济对电网规划和发展的影响[J].中国电力,2010,43(3)：1-4.
[31]田廓,邱柳青,曾鸣.基于动态碳排放价格的电网规划模型[J].中国电机工程学报,2012,32(4)：57-64.
[32]Campbell Hector, Montero Gisela, Perez Carlos, et al. Efficient energy utilization and environmental issues applied to power planning[J]. Energy Policy,2011,39: 3630-3637.
[33]Roh Jae Hyung, Shahidehpour Mohammad, Fu Yong. Market-based coordination of transmission and generation capacity planning[J]. IEEE Transactions on Power Systems,2007,22(4):1406-1419.
[34]Alizadeh B, Jadid S. Reliability constrained coordination of generation and transmission expansion planning in power systems using mixed integer programming[J]. IET Genration Transmission & Distribution,2011,5(9):948-960.
[35]Sharan Ishan, Balasubramanian R. Integrated generation and transmission expansion planning including power and fuel transportation constraints[J]. Energy Policy,2012, 43:275-284.
[36]Chakraborty Shantanu, Senjyu Tomonobu, Saber Ahmed Yousuf, et al. A fuzzy binary clustered particle swarm optimization strategy for thermal unit commitment problem with wind power integration[J]. IEEJ Transactions on Electrical and Electronic Engineering,2012,7(5):478-486.
[37]Jiang Ruiwei, Wang Jianhui, Guan Yongpei. Robust unit commitment with wind power and pumped storage hydro[J]. IEEE Transactions on Power Systems,2012, 27(2):800-810.
[38]Wang Qianfan, Guan Yongpei, Wang Jianhui. A chance-constrained two-stage stochastic pogram for unit commitment with uncertain wind power output[J]. IEEE Transactions on Power Systems,2012,27(1):206-215.
[39]周任军,姚龙华,童小娇,等.采用条件风险方法的含风电系统安全经济调度[J].中国电机工程学报,2012,32(1)：56-63.
[40]袁铁江,晁勤,吐尔逊·伊不拉音,等.大规模风电并网电力系统动态清洁经济优化调度的建模[J].中国电机工程学报,2010,30(31)：7-13.
[41]于大洋,宋曙光,张波,等.区域电网电动汽车充电与风电协同调度的分析[J].电力系统自动化,2011,35(14)：24-29.
[42]赵俊华,文福栓,薛禹胜,等.计及电动汽车和风电出力不确定性的随机经济调 度[J].电力系统自动化,2010,34(20)：22-29.
[43]Massimo Filippini. Short-and long-run time-of-use price elasticities in Swiss residential electricity demand[J]. Energy Policy,2011,39(10):5811-5817.
[44]刘健,王双虎,明正峰.需求侧负荷管理中最优错峰计划的生成[J].电力系统自动化,2006,30(8)：47-51.
[45]谭忠富,谢品杰,王绵斌,等.提高电能使用效率的可中断电价与峰谷分时电价的联合优化设计[J].电工技术学报,2009,24(5)：161-168.
[46]谭忠富,于超,姜海洋.用户端峰谷分时电价对发电端节煤影响分析模型[J].系统工程理论与实践,2009,29(10)：94-101.
[47]谭忠富,王绵斌,张蓉,等.发电侧与供电侧峰谷分时电价联动的分级优化模型[J].电力系统自动化,2007,31(21)：26-34.
[48]谭忠富,陈广娟,赵建保,等.以节能调度为导向的发电侧与售电侧峰谷分时电价联合优化模型[J].中国电机工程学报,2009,29(1)：55-62.
[49]Gerber Annelies, Qadrdan Meysam, Chaudry Modassar. A 2020 GB transmission network study using dispersed wind farm power output[J]. Renewable Energy,2012, 37(1):124-132.
[50]Rombauts Yannick, Delarue Erik, D'haeseleers William. Optimal portfolio-theory-based allocation of wind power:Taking into account cross-border transmission-capacity constraints[J]. renewable energy,2011,36(9):2374-2387.
[51]张丽英,叶廷路,辛耀中,等.大规模风电接入电网的相关问题及措施[J].中国电机工程学报,2010,30(25)：1-9.
[52]汪宁渤,王建东,何世恩.酒泉风电跨区消纳模式及其外送方案[J].电力系统自动化,2011,35(22)：82-89.
[53]白建华,辛颂旭,贾德香,等.中国风电开发消纳及输送相关重大问题研究[J].电网与清洁能源,2010,26(1)：14-17.
[54]陈震寰,陈永华,行舟,等.大型集群风电有功智能控制系统控制策略(二)风火电“打捆”外送协调控制[J].电力系统自动化,2011,35(21)：12-15.
[55]郭小江,马世英,中洪,等.大规模风电直流外送方案与系统稳定控制策略[J].电力系统自动化,2012,36(15)：107-115.
[56]华文,徐政.风电火电打捆送出时的输电容量优化方法[J].电力系统保护与控制,2012,40(8)：121-125.
[57]Ault G.W., Bell K.R.W., Galloway S.J. Calculation of economic transmission connection capacity for wind power generation[J]. IET Renewable Power Generation, 2007,1(1):61-69.
[58]Ahmidi Amir, Guillaud Xavier, Besanger Yvon. A multilevel approach for optimal participating of wind farms at reactive power balancing in transmission power system[J]. IEEE Systems Journal,2012,6(2):260-269.
[59]吴耀文,马溪原,方华亮,等.大规模风电特高压专用通道落点优选方法[J].中国电机工程学报,2012,32(1)：9-16.
[60]张宁,康重庆,周宇田,等.风电与常规电源联合外送的受端可信容量研究[J].中国电机工程学报,2012,32(10)：72-79.
[61]朱柯丁,宋艺航,谭忠富,等.中国风电并网现状及风电节能减排效益分析[J].中国电力,2011,44(6)：67-70.
[62]沈又幸,刘琳,曾鸣.风电社会效益的评价模型及其应用研究[J].华东电力,2009,37(5)：852-855.
[63]李俊峰,施鹏飞,高虎.中国风电发展报告2010[M].海口：海南出版社,2010：87-88.
[64]Liao Gwo-Ching. A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power[J]. Energy,2011,36(2):1018-1029.
[65]李智,韩学山,杨明,等.计及接纳风电能力的电网调度模型[J].电力系统自动化,2010,34(19)：15-19.
[66]张粒子,周娜,王楠.大规模风电接入电力系统调度模式的经济性比较[J].电力系统自动化,2011,35(22)：105-110.
[67]吴淳.风电对电力系统调频和备用的影响研究[J].华东电力,2011,39(6)：993-996.
[68]白兴忠,江国琪,王建学,等.风电接入对西北电网辅助服务的影响[J].中国电力,2009,42(12)：73-76.
[69]王彩霞,乔颖,鲁宗相.考虑风电效益的风火互济系统旋转备用确定方式[J].电力系统自动化,2012,36(4)：16-21.
[70]Radzik Tadeusz. A new look at the role of players' weights in the weighted Shapley value[J]. European Journal of Operational Resarch,2012,223(2):407-416.
[71]Tol Richard S. J. Shapley values for assessing research production and impact of schools and scholars[J]. Scientometrics,2012,90(3):763-780.
[72]李莉,丁亚伟,谭忠富,等.发电权交易机制下基于合作博弈的利润分配模型[J].华东电力,2009,37(11)：1803-1806.
[73]刘建芬,胡奇英,李华.基于Shapley值法的VMI下合作企业间的费用分担策略[J].系统工程,2005,23(9)：50-54.
[74]杨洪明,段献忠.双边交易模式下基于Aumann-Shapley值的阻塞费用分摊方法研究[J].中国电机工程学报,2002,22(11)：59-63.
[75]郑立群,吴育华,夏庆Aumann-Shapley定价公式在分配问题中的应用[J].系统工程学报,2001,30(2)：150-153.
[76]周兴华,杜松怀.双边交易电力市场下基于核仁理论的网损分摊方法[J].中国电机工程学报,2005,25(1)：60-65.
[77]杨继君,许维胜,吴启迪,等.基于改进核心法的合作博弈在供应链中的应用[J].工业工程与管理,2008,(4)：15-18
[78]Sim Kwang Mong, Guo Yuanyuan, Shi Benyun. BLGAN:bayesian learning and genetic algorithm for supporting negotiation with incomplete information[J]. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics,2009,39(1): 198-211.
[79]Buffett Scott, Spencer Bruce. A Bayesian classifier for learning opponents' preferences in multi-object automated negotiation[J]. Electronic Commerce Research and Applications,2007,6(3):274-284.
[80]宁红云,刘金兰,张德干.基于对手不完全信息的订单在线智能协商模型[J].计算机应用,2009,29(1)：221-223.
[81]谭忠富,于超,姜海洋,等.煤炭供应商与发电商之间合约谈判风险收益平衡优化模型[J].系统工程理论与实践,2011,31(11)：2108-2114.
[82]谭忠富,李莉,王成文.迭代竞价机制下发电商的贝叶斯学习模型[J].中国电机工程学报,2008,28(25)：118-124.
[83]谭忠富,李莉,王建军,等.多智能体代理下电力双边谈判中的模糊贝叶斯学习模型[J].中国电机工程学报,2009,29(7)：106-113.
[84]黎灿兵,康重庆,夏清,等.发电权交易及其机理分析[J].电力系统自动化,2003,27(6)：13-18.
[85]尚金成,何洋.基于节能减排的发电权交易理论及应用(二)发电权交易分析及应用[J].电力系统自动化,2009,33(13)：37-42.
[86]尚金成.基于节能减排的发电权交易理论及应用(一)发电权交易理论[J].电力系统自动化,2009,33(12)：46-52.
[87]陈启鑫,康重庆,程旭东,等.考虑阻塞管理的发电权交易模型及其网络流算法[J].中国电机工程学报,2008,28(34)：106-111.
[88]肖健,文福栓.发电权交易的阻塞调度[J].电力系统自动化,2008,32(18)：24-29.
[89]黄大为,刘志向,杨春雨,等.计及网损成本的发电权交易模式[J].电力系统自动化,2010,34(5)：38-42.
[90]王雅娟,王先甲.一种激励相容的发电权交易双边拍卖机制[J].电力系统自动化,2009,33(22)：25-28.
[91]莫莉,周建中,李清清,等.基于委托代理模型的发电权交易模式[J].电力系统 自动化,2008,32(2)：30-34.
[92]姚建刚,周启亮,张佳启,等.基于期权理论的发电权交易模型[J].中国电机工程学报,2005,25(21)：76-81.
[93]Xiao Jian, Wen Fushuan, Huang Jiansheng. Congestion dispatch in a hybrid generation-rights market[J]. European Transactions on Electrical Power,2011,21(1): 1046-1053.
[94]肖健,文福栓.混合发电权交易市场环境下的阻塞协调调度[J].电力系统自动化,2010,34(8)：44-48.
[95]柳瑞禹,陈岸.发电权交易的定价机制与竞价规则改进[J].武汉大学学报(工学版),2010,43(6)：813-816.
[96]伍玉林,文福栓,丁剑鹰,等.发电公司在发电权交易市场的竞价策略初探[J].电力系统自动化,2010,34(17)：6-11.
[97]舒隽,张丽娟,张粒子,等.发电权竞价交易的两阶段方法[J].电网技术,2011,35(11)：200-205.
[98]Andreas G. Vlachos, Pandelis N. Biskas. Balancing Supply and Demand under Mixed Pricing Rules in Multi-Area Electricity Markets[J]. IEEE Transactions on Power Systems,2011,26(3):1444-1453.
[99]K.H. Chung, B.H. Kim, D. Hur. Multi-area Generation Scheduling Algorithm with Regionally Distributed Optimal Power Fow Using Alternating Direction Method[J]. Electrical Power and Energy Systems,2011,33(9):1527-1535.
[100]姜海洋,李莉,谭忠富,等.减排与输电约束下区域间发电功率互换优化模型[J].电网技术,2010,34(6)：64-72.
[101]BP Group. BP Statistical review of world energy 2012[M/OL]. [2012-08-25]. http://www.bp.com/product anding.do?categoryId=9041910&contentId=7075397.
[102]IEA. CO2 emissions from fuel combustion highlights[M]. Paris:International Energy Agency,2011.
[103]中华人民共和国统计局.中国统计年鉴2011年[M].北京：中国统计出版社,2011.
[104]徐帆,姚建国,耿建,等.机组耗量特性的混合整数模型建立与分析[J].电力系统自动化,2010,34(10)：45-50.
[105]国务院办公厅.国办发[2007]53号文件：国务院办公厅关于转发发展改革委等部门节能发电调度办法(试行)的通知[EB/OL].2007-12-31. http://www.gov.cn/zwgk/2007-08/07/content_708486.
[106]中国电力企业联合会.2010年电力工业统计资料汇编[M].北京：中国电力出版社,2011.
[107]林伯强.中国电力工业发展：改革进程与配套改革[J].管理世界,2005,(8)： 65-79.
[108]国家发改委.关于建立煤电价格联动机制的意见(发改价格[2004]2909号)[EB/OL]. [2012-4-2] http://nyj.ndrc.gov.cn/nyfhb/nyfhb4/nyfhb47/t20070112_110474.htm.
[109]He Y.X, Zhang S.L, Yang L.Y, et al. Economic analysis of coal price-electricity price adjustment in China based on the CGE model[J]. Energy Policy,2010,38(11): 6629-6637.
[110]Jiao J.L, Ge H.Z, Wei Y.M. Impact analysis of China's coal-electricity price linkage mechanism:Results from a game model[J]. Journal of Policy Modeling,2010,32(4): 574-588.
[111]康长安,杨彤.煤电价格联动的讨价还价博弈分析[J].中国煤炭,2012,(02)：35-37.
[112]张明文.中国煤电产业链协调发展的优化模型研究[D].北京：华北电力大学,2009.
[113]徐鸣哲,刘丽丽.基于双重加价模型的煤电价格联动分析[J].苏州大学学报,2011,(4)：129-132.
[114]叶泽,陈星文,蔡建刚.电煤市场中买方市场集中度对均衡价格的影响分析[J].中国工业经济,2012,(2)：68-78.
[115]罗鑫,张粒子.煤电价格传导机制分析及政策建议[J].能源技术经济,2010,22(2)：19-22.
[116]洪结银.完善煤电价格联动政策的对策研究[J].价格理论与实践,2011,(9)：27-28.
[117]王绵斌,谭忠富,关勇,等.提高电能效率的自备电厂并网备用容量费用计算模型[J].系统工程理论与实践,2010,30(1)：151-156.
[118]郭亚军.综合评价理论与方法[M].北京：科学出版社,2002.
[119]郑国强,鲍海,陈树勇.基于近似线性规划的风电场穿透功率极限优化的改进算法[J].中国电机工程学报,2004,10(5)：69-71.
[120]Luis Baringo, Antonio J. Conejo. Transmission and wind power investment[J]. IEEE Transactions on Power Systems,2012,27(2):885-893.
[121]包能胜,胡光旺,倪维斗.风电与燃气轮机发电互补系统结构与容量配比的研究[J].太阳能学报,2007,28(2)：189-195.
[122]Lena Neij. Cost development of future technologies for power generation:A study based on experience curves and complementary bottom-up assessments[J]. Energy Policy,2008,36(6):2200-2211.
[123]Nadejda Komendantova, Anthony Patt, Keith Williges. Solar power investment in North Africa:Reducing perceived risks[J]. Renewable and Sustainable Energy Reviews,2011,15(9):4829-4835.
[124]K. Chandrasekaran, S. Hemamalini, Sishaj P. Simon, et al. Thermal unit commitment using binary/real coded artificial bee colony algorithm[J]. Electric Power Systems Research,2012,84(1):109-119.
[125]Lopez JA, Ceciliano-Meza JL, Moya IG, et al. A MIQCP formulation to solve the unit commitment problem for large-scale power systems[J]. Electrical Power and Energy Systems,2012,36(1):68-75.
[126]Hadji MM; Vahidi B. A Solution to the Unit Commitment Problem Using Imperialistic Competition Algorithm[J]. IEEE Transactions on Power Systems,2012, 27(1):117-124.
[127]Gaing ZL, Lin GN. Unit Commitment With Security Assessment Using Chaotic PSO Algorithm[J]. Journal of Circuits Systems and Computers,2011,20(7): 1357-1376.
[128]娄素华,余欣梅,熊信艮,等.电力系统机组启停优化问题的改进DPSO算法[J].中国电机工程学报,2005,25(8)：30-35.
[129]黎静华,韦化.节能发电调度计划多Agent制定系统[J].电网技术,2011,35(5)：90-96.
[130]张舒,胡泽春,宋永华,等.基于网损因子迭代的安全约束机组组合算法[J].中国电机工程学报,2012,32(7)：76-82.
[131]钟永光,贾晓菁,钱颖,等.系统动力学[M].北京：科学出版社,2013.
[2]Liu Jinpeng, Niu Dongxiao, Song Xiaohua. The energy supply and demand pattern of China:A review of evolution and sustainable development[J]. Renewable & Sustainable Energy Review,2013,25,220-228.
[3]张运洲.我国跨区域电力资源配置前景分析[J].中国电力,2004,37(9)：5-7.
[4]Froggatt Antony. The climate and energy security implications of coal demand and supply in Asia and Europe[J]. Asia Europe Journal,2013,11(3):285-303.
[5]Sun Mei, Han Dun, Li Dandan, et al. The general evolving model for energy supply-demand network with local-world[J]. International Journal of Modern Physics C,24(10):75-89.
[6]王建军,李莉,谭忠富,等.电力需求侧响应利益联动机制的系统动力学模拟[J].系统工程理论与实践,2011,31(12)：2287-2295.
[7]Kahen G M, Lehman M, Ramil J F, et al. System dynamics modelling of software evolution proeesses for policy investigation:Approach and example[J]. Journal of Systems and Software,2001,50(3):271-281.
[8]Saleh M, Oliva R, Kampmann C E, et al. A comprehensive analytical approaeh for policy analysis of system dynamics models[J]. European Journal of Operational Researeh,2010,203(3):673-683.
[9]Shen Q P, Chen Q, Tang B S, et al. A system dynamics model for the sustainable land use planning and development[J]. Habitat Intern ational,2009,33(1):15-25.
[10]李连德.中国能源供需的系统动力学研究[D].沈阳：东北大学,2009.
[11]Anindya Bhattacharya, Satoshi Kojima. Power sector investment risk and renewable energy:A Japanese case study using portfolio risk optimization method[J]. Energy Policy,2012,40:69-80.
[12]Lin Fan, Catherine S. Norman, Anthony G. Patt. Electricity capacity investment under risk aversion:A case study of coal, gas, and concentrated solar power[J]. Energy Economics,2012,34(1):54-61.
[13]Zhang Dongjie, Liu Pei, Ma Linwei, et al. A multi-period modelling and optimization approach to the planning of China's power sector with consideration of carbon dioxide mitigation[J]. Computers and Chemical Engineering,2012,37: 227-247.
[14]Liu Ye, Huang Guohe, Cai Yanpeng, et al. An inexact mix-integer two-stage linear programming model for supporting the management of a low-carbon energy system in China[J]. Energies,2011,4(10):1657-1686.
[15]Chen C, Li Y P, Huang G H, et al. A robust optimization method for planning regional-scale electric power systems and managing carbon dioxide[J]. Electrical Power and Energy Systems,2012,40(1):70-84.
[16]Tolis Athanasios I., Rentizelas Athanasios A.. An impact assessment of electricity and emission allowances pricing in optimised expansion planning of power sector portfolios[J]. Applied Eneygy,2011,88(11):3791-3806.
[17]Masoud Hasani-Marzooni, Seyed Hamid Hosseini. Dynamic model for market-based capacity investment decision considering stochastic characteristic of wind power[J]. Renewable Energy,2011,36(8):2205-2219.
[18]Yu Y X, Wang J R, Lv X Y. Security value based expansion planning of power system with integration of large-scale wind power[J]. Science China-Technological Sciences,2012,55(7):1908-1922.
[19]Alonso Monica, Amaris Hortensia, Alvarez-Ortega C. A multiobjective approach for reactive power planning in networks with wind power generation[J]. Renewable Energy,2012,37(1):180-191.
[20]袁建党,袁铁江,晁勤,等.电力市场环境下大规模风电并网系统电源规划研究[J].电力系统保护与控制,2011,39(5)：22-26.
[21]Shrestha G B, Fonseka P A J. Congestion-driven transmission expansion in competitive power markets[J]. IEEE Trans, on Power Systems,2003,19(3): 1658-1665.
[22]Bent Russell, Toole G. Loren, Berscheid Alan. Transmission network expansion planning with complex power Flow Models[J]. IEEE Transactions on Power Systems,2012,27(2):904-912.
[23]Zhao Jun Hua, Foster John, Dong Zhao Yang, et al. Flexible Transmission Network Planning Considering Distributed Generation Impacts[J]. IEEE Transactions on Power Systems,2011,26(3):1434-1443.
[24]Leou Rong-ceng. A multi-year transmission planning under a deregulated market[J]. International Journal of Electrical Power & Energy Systems,2011,33(3):708-714.
[25]Fan Hong; Cheng Hao-zhong. Multistage transmission network expansion planning in competitive electricity market based on bi-level programming method[J]. European Transactions on Electrical Power,2011,21(5):1719-1730.
[26]高赐威,程浩忠,王旭.考虑场景发生概率的柔性约束电网规划模型[J].中国电机工程学报,2004,24(11)：34-38.
[27]Raby Mauricio, Rios Sebastion, Jerardino Samuel. Integrating large wind farms into transmission planning of hydrothermal system[J]. Journal of Energy Engineering-ASCE,2009,135(3):89-97.
[28]Yu H, Chung C Y, Wong K P, et al. A Chance Constrained Transmission Network Expansion Planning Method With Consideration of Load and Wind Farm Uncertainties[J]. IEEE Transactions on Power Systems,2009,24(3):1568-1576.
[29]钟庆,吴捷,黄武忠,等.动态规划在电力建设项目投资决策中的应用[J].电网技术,2002,26(8)：48-51.
[30]孙寿广.低碳经济对电网规划和发展的影响[J].中国电力,2010,43(3)：1-4.
[31]田廓,邱柳青,曾鸣.基于动态碳排放价格的电网规划模型[J].中国电机工程学报,2012,32(4)：57-64.
[32]Campbell Hector, Montero Gisela, Perez Carlos, et al. Efficient energy utilization and environmental issues applied to power planning[J]. Energy Policy,2011,39: 3630-3637.
[33]Roh Jae Hyung, Shahidehpour Mohammad, Fu Yong. Market-based coordination of transmission and generation capacity planning[J]. IEEE Transactions on Power Systems,2007,22(4):1406-1419.
[34]Alizadeh B, Jadid S. Reliability constrained coordination of generation and transmission expansion planning in power systems using mixed integer programming[J]. IET Genration Transmission & Distribution,2011,5(9):948-960.
[35]Sharan Ishan, Balasubramanian R. Integrated generation and transmission expansion planning including power and fuel transportation constraints[J]. Energy Policy,2012, 43:275-284.
[36]Chakraborty Shantanu, Senjyu Tomonobu, Saber Ahmed Yousuf, et al. A fuzzy binary clustered particle swarm optimization strategy for thermal unit commitment problem with wind power integration[J]. IEEJ Transactions on Electrical and Electronic Engineering,2012,7(5):478-486.
[37]Jiang Ruiwei, Wang Jianhui, Guan Yongpei. Robust unit commitment with wind power and pumped storage hydro[J]. IEEE Transactions on Power Systems,2012, 27(2):800-810.
[38]Wang Qianfan, Guan Yongpei, Wang Jianhui. A chance-constrained two-stage stochastic pogram for unit commitment with uncertain wind power output[J]. IEEE Transactions on Power Systems,2012,27(1):206-215.
[39]周任军,姚龙华,童小娇,等.采用条件风险方法的含风电系统安全经济调度[J].中国电机工程学报,2012,32(1)：56-63.
[40]袁铁江,晁勤,吐尔逊·伊不拉音,等.大规模风电并网电力系统动态清洁经济优化调度的建模[J].中国电机工程学报,2010,30(31)：7-13.
[41]于大洋,宋曙光,张波,等.区域电网电动汽车充电与风电协同调度的分析[J].电力系统自动化,2011,35(14)：24-29.
[42]赵俊华,文福栓,薛禹胜,等.计及电动汽车和风电出力不确定性的随机经济调 度[J].电力系统自动化,2010,34(20)：22-29.
[43]Massimo Filippini. Short-and long-run time-of-use price elasticities in Swiss residential electricity demand[J]. Energy Policy,2011,39(10):5811-5817.
[44]刘健,王双虎,明正峰.需求侧负荷管理中最优错峰计划的生成[J].电力系统自动化,2006,30(8)：47-51.
[45]谭忠富,谢品杰,王绵斌,等.提高电能使用效率的可中断电价与峰谷分时电价的联合优化设计[J].电工技术学报,2009,24(5)：161-168.
[46]谭忠富,于超,姜海洋.用户端峰谷分时电价对发电端节煤影响分析模型[J].系统工程理论与实践,2009,29(10)：94-101.
[47]谭忠富,王绵斌,张蓉,等.发电侧与供电侧峰谷分时电价联动的分级优化模型[J].电力系统自动化,2007,31(21)：26-34.
[48]谭忠富,陈广娟,赵建保,等.以节能调度为导向的发电侧与售电侧峰谷分时电价联合优化模型[J].中国电机工程学报,2009,29(1)：55-62.
[49]Gerber Annelies, Qadrdan Meysam, Chaudry Modassar. A 2020 GB transmission network study using dispersed wind farm power output[J]. Renewable Energy,2012, 37(1):124-132.
[50]Rombauts Yannick, Delarue Erik, D'haeseleers William. Optimal portfolio-theory-based allocation of wind power:Taking into account cross-border transmission-capacity constraints[J]. renewable energy,2011,36(9):2374-2387.
[51]张丽英,叶廷路,辛耀中,等.大规模风电接入电网的相关问题及措施[J].中国电机工程学报,2010,30(25)：1-9.
[52]汪宁渤,王建东,何世恩.酒泉风电跨区消纳模式及其外送方案[J].电力系统自动化,2011,35(22)：82-89.
[53]白建华,辛颂旭,贾德香,等.中国风电开发消纳及输送相关重大问题研究[J].电网与清洁能源,2010,26(1)：14-17.
[54]陈震寰,陈永华,行舟,等.大型集群风电有功智能控制系统控制策略(二)风火电“打捆”外送协调控制[J].电力系统自动化,2011,35(21)：12-15.
[55]郭小江,马世英,中洪,等.大规模风电直流外送方案与系统稳定控制策略[J].电力系统自动化,2012,36(15)：107-115.
[56]华文,徐政.风电火电打捆送出时的输电容量优化方法[J].电力系统保护与控制,2012,40(8)：121-125.
[57]Ault G.W., Bell K.R.W., Galloway S.J. Calculation of economic transmission connection capacity for wind power generation[J]. IET Renewable Power Generation, 2007,1(1):61-69.
[58]Ahmidi Amir, Guillaud Xavier, Besanger Yvon. A multilevel approach for optimal participating of wind farms at reactive power balancing in transmission power system[J]. IEEE Systems Journal,2012,6(2):260-269.
[59]吴耀文,马溪原,方华亮,等.大规模风电特高压专用通道落点优选方法[J].中国电机工程学报,2012,32(1)：9-16.
[60]张宁,康重庆,周宇田,等.风电与常规电源联合外送的受端可信容量研究[J].中国电机工程学报,2012,32(10)：72-79.
[61]朱柯丁,宋艺航,谭忠富,等.中国风电并网现状及风电节能减排效益分析[J].中国电力,2011,44(6)：67-70.
[62]沈又幸,刘琳,曾鸣.风电社会效益的评价模型及其应用研究[J].华东电力,2009,37(5)：852-855.
[63]李俊峰,施鹏飞,高虎.中国风电发展报告2010[M].海口：海南出版社,2010：87-88.
[64]Liao Gwo-Ching. A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power[J]. Energy,2011,36(2):1018-1029.
[65]李智,韩学山,杨明,等.计及接纳风电能力的电网调度模型[J].电力系统自动化,2010,34(19)：15-19.
[66]张粒子,周娜,王楠.大规模风电接入电力系统调度模式的经济性比较[J].电力系统自动化,2011,35(22)：105-110.
[67]吴淳.风电对电力系统调频和备用的影响研究[J].华东电力,2011,39(6)：993-996.
[68]白兴忠,江国琪,王建学,等.风电接入对西北电网辅助服务的影响[J].中国电力,2009,42(12)：73-76.
[69]王彩霞,乔颖,鲁宗相.考虑风电效益的风火互济系统旋转备用确定方式[J].电力系统自动化,2012,36(4)：16-21.
[70]Radzik Tadeusz. A new look at the role of players' weights in the weighted Shapley value[J]. European Journal of Operational Resarch,2012,223(2):407-416.
[71]Tol Richard S. J. Shapley values for assessing research production and impact of schools and scholars[J]. Scientometrics,2012,90(3):763-780.
[72]李莉,丁亚伟,谭忠富,等.发电权交易机制下基于合作博弈的利润分配模型[J].华东电力,2009,37(11)：1803-1806.
[73]刘建芬,胡奇英,李华.基于Shapley值法的VMI下合作企业间的费用分担策略[J].系统工程,2005,23(9)：50-54.
[74]杨洪明,段献忠.双边交易模式下基于Aumann-Shapley值的阻塞费用分摊方法研究[J].中国电机工程学报,2002,22(11)：59-63.
[75]郑立群,吴育华,夏庆Aumann-Shapley定价公式在分配问题中的应用[J].系统工程学报,2001,30(2)：150-153.
[76]周兴华,杜松怀.双边交易电力市场下基于核仁理论的网损分摊方法[J].中国电机工程学报,2005,25(1)：60-65.
[77]杨继君,许维胜,吴启迪,等.基于改进核心法的合作博弈在供应链中的应用[J].工业工程与管理,2008,(4)：15-18
[78]Sim Kwang Mong, Guo Yuanyuan, Shi Benyun. BLGAN:bayesian learning and genetic algorithm for supporting negotiation with incomplete information[J]. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics,2009,39(1): 198-211.
[79]Buffett Scott, Spencer Bruce. A Bayesian classifier for learning opponents' preferences in multi-object automated negotiation[J]. Electronic Commerce Research and Applications,2007,6(3):274-284.
[80]宁红云,刘金兰,张德干.基于对手不完全信息的订单在线智能协商模型[J].计算机应用,2009,29(1)：221-223.
[81]谭忠富,于超,姜海洋,等.煤炭供应商与发电商之间合约谈判风险收益平衡优化模型[J].系统工程理论与实践,2011,31(11)：2108-2114.
[82]谭忠富,李莉,王成文.迭代竞价机制下发电商的贝叶斯学习模型[J].中国电机工程学报,2008,28(25)：118-124.
[83]谭忠富,李莉,王建军,等.多智能体代理下电力双边谈判中的模糊贝叶斯学习模型[J].中国电机工程学报,2009,29(7)：106-113.
[84]黎灿兵,康重庆,夏清,等.发电权交易及其机理分析[J].电力系统自动化,2003,27(6)：13-18.
[85]尚金成,何洋.基于节能减排的发电权交易理论及应用(二)发电权交易分析及应用[J].电力系统自动化,2009,33(13)：37-42.
[86]尚金成.基于节能减排的发电权交易理论及应用(一)发电权交易理论[J].电力系统自动化,2009,33(12)：46-52.
[87]陈启鑫,康重庆,程旭东,等.考虑阻塞管理的发电权交易模型及其网络流算法[J].中国电机工程学报,2008,28(34)：106-111.
[88]肖健,文福栓.发电权交易的阻塞调度[J].电力系统自动化,2008,32(18)：24-29.
[89]黄大为,刘志向,杨春雨,等.计及网损成本的发电权交易模式[J].电力系统自动化,2010,34(5)：38-42.
[90]王雅娟,王先甲.一种激励相容的发电权交易双边拍卖机制[J].电力系统自动化,2009,33(22)：25-28.
[91]莫莉,周建中,李清清,等.基于委托代理模型的发电权交易模式[J].电力系统 自动化,2008,32(2)：30-34.
[92]姚建刚,周启亮,张佳启,等.基于期权理论的发电权交易模型[J].中国电机工程学报,2005,25(21)：76-81.
[93]Xiao Jian, Wen Fushuan, Huang Jiansheng. Congestion dispatch in a hybrid generation-rights market[J]. European Transactions on Electrical Power,2011,21(1): 1046-1053.
[94]肖健,文福栓.混合发电权交易市场环境下的阻塞协调调度[J].电力系统自动化,2010,34(8)：44-48.
[95]柳瑞禹,陈岸.发电权交易的定价机制与竞价规则改进[J].武汉大学学报(工学版),2010,43(6)：813-816.
[96]伍玉林,文福栓,丁剑鹰,等.发电公司在发电权交易市场的竞价策略初探[J].电力系统自动化,2010,34(17)：6-11.
[97]舒隽,张丽娟,张粒子,等.发电权竞价交易的两阶段方法[J].电网技术,2011,35(11)：200-205.
[98]Andreas G. Vlachos, Pandelis N. Biskas. Balancing Supply and Demand under Mixed Pricing Rules in Multi-Area Electricity Markets[J]. IEEE Transactions on Power Systems,2011,26(3):1444-1453.
[99]K.H. Chung, B.H. Kim, D. Hur. Multi-area Generation Scheduling Algorithm with Regionally Distributed Optimal Power Fow Using Alternating Direction Method[J]. Electrical Power and Energy Systems,2011,33(9):1527-1535.
[100]姜海洋,李莉,谭忠富,等.减排与输电约束下区域间发电功率互换优化模型[J].电网技术,2010,34(6)：64-72.
[101]BP Group. BP Statistical review of world energy 2012[M/OL]. [2012-08-25]. http://www.bp.com/product anding.do?categoryId=9041910&contentId=7075397.
[102]IEA. CO2 emissions from fuel combustion highlights[M]. Paris:International Energy Agency,2011.
[103]中华人民共和国统计局.中国统计年鉴2011年[M].北京：中国统计出版社,2011.
[104]徐帆,姚建国,耿建,等.机组耗量特性的混合整数模型建立与分析[J].电力系统自动化,2010,34(10)：45-50.
[105]国务院办公厅.国办发[2007]53号文件：国务院办公厅关于转发发展改革委等部门节能发电调度办法(试行)的通知[EB/OL].2007-12-31. http://www.gov.cn/zwgk/2007-08/07/content_708486.
[106]中国电力企业联合会.2010年电力工业统计资料汇编[M].北京：中国电力出版社,2011.
[107]林伯强.中国电力工业发展：改革进程与配套改革[J].管理世界,2005,(8)： 65-79.
[108]国家发改委.关于建立煤电价格联动机制的意见(发改价格[2004]2909号)[EB/OL]. [2012-4-2] http://nyj.ndrc.gov.cn/nyfhb/nyfhb4/nyfhb47/t20070112_110474.htm.
[109]He Y.X, Zhang S.L, Yang L.Y, et al. Economic analysis of coal price-electricity price adjustment in China based on the CGE model[J]. Energy Policy,2010,38(11): 6629-6637.
[110]Jiao J.L, Ge H.Z, Wei Y.M. Impact analysis of China's coal-electricity price linkage mechanism:Results from a game model[J]. Journal of Policy Modeling,2010,32(4): 574-588.
[111]康长安,杨彤.煤电价格联动的讨价还价博弈分析[J].中国煤炭,2012,(02)：35-37.
[112]张明文.中国煤电产业链协调发展的优化模型研究[D].北京：华北电力大学,2009.
[113]徐鸣哲,刘丽丽.基于双重加价模型的煤电价格联动分析[J].苏州大学学报,2011,(4)：129-132.
[114]叶泽,陈星文,蔡建刚.电煤市场中买方市场集中度对均衡价格的影响分析[J].中国工业经济,2012,(2)：68-78.
[115]罗鑫,张粒子.煤电价格传导机制分析及政策建议[J].能源技术经济,2010,22(2)：19-22.
[116]洪结银.完善煤电价格联动政策的对策研究[J].价格理论与实践,2011,(9)：27-28.
[117]王绵斌,谭忠富,关勇,等.提高电能效率的自备电厂并网备用容量费用计算模型[J].系统工程理论与实践,2010,30(1)：151-156.
[118]郭亚军.综合评价理论与方法[M].北京：科学出版社,2002.
[119]郑国强,鲍海,陈树勇.基于近似线性规划的风电场穿透功率极限优化的改进算法[J].中国电机工程学报,2004,10(5)：69-71.
[120]Luis Baringo, Antonio J. Conejo. Transmission and wind power investment[J]. IEEE Transactions on Power Systems,2012,27(2):885-893.
[121]包能胜,胡光旺,倪维斗.风电与燃气轮机发电互补系统结构与容量配比的研究[J].太阳能学报,2007,28(2)：189-195.
[122]Lena Neij. Cost development of future technologies for power generation:A study based on experience curves and complementary bottom-up assessments[J]. Energy Policy,2008,36(6):2200-2211.
[123]Nadejda Komendantova, Anthony Patt, Keith Williges. Solar power investment in North Africa:Reducing perceived risks[J]. Renewable and Sustainable Energy Reviews,2011,15(9):4829-4835.
[124]K. Chandrasekaran, S. Hemamalini, Sishaj P. Simon, et al. Thermal unit commitment using binary/real coded artificial bee colony algorithm[J]. Electric Power Systems Research,2012,84(1):109-119.
[125]Lopez JA, Ceciliano-Meza JL, Moya IG, et al. A MIQCP formulation to solve the unit commitment problem for large-scale power systems[J]. Electrical Power and Energy Systems,2012,36(1):68-75.
[126]Hadji MM; Vahidi B. A Solution to the Unit Commitment Problem Using Imperialistic Competition Algorithm[J]. IEEE Transactions on Power Systems,2012, 27(1):117-124.
[127]Gaing ZL, Lin GN. Unit Commitment With Security Assessment Using Chaotic PSO Algorithm[J]. Journal of Circuits Systems and Computers,2011,20(7): 1357-1376.
[128]娄素华,余欣梅,熊信艮,等.电力系统机组启停优化问题的改进DPSO算法[J].中国电机工程学报,2005,25(8)：30-35.
[129]黎静华,韦化.节能发电调度计划多Agent制定系统[J].电网技术,2011,35(5)：90-96.
[130]张舒,胡泽春,宋永华,等.基于网损因子迭代的安全约束机组组合算法[J].中国电机工程学报,2012,32(7)：76-82.
[131]钟永光,贾晓菁,钱颖,等.系统动力学[M].北京：科学出版社,2013.
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